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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Key Constructs for Reasonable Confidence in System Validation Programs

This paper presents four key constructs developed in preparing IEEE Std P2411TM, Human Factors Engineering Guide for the Validation of System Designs and Integrated Systems Operations at Nuclear Facilities for submission. These constructs reflect judgments that responsible parties make in order to bring validation to closure. Such judgments weigh competing concerns and cost-benefits for stakeholders. Improved processes and methods may support such judgments but cannot alone eliminate uncertainty. Stating and clarifying these constructs aims to reduce uncertainty in the validation process, to better prepare the implementers and reviewers of future validation programs, both in the nuclear industry and beyond. Reasonable Confidence – A proof standard, as used to reach conclusions in a legal case. Legal proof standards are bounded between “preponderance of evidence” and “beyond reasonable doubt”. Reasonable confidence is comparable to an intermediate legal proof standard of “clear and convincing evidence.” Representative Test Set – A collection of scenarios of sufficient variety to represent the anticipated range of operational conditions, events, evolutions, and activities for validating the system(s) under test. Dispositive vs. Diagnostic Criteria – Relevant performance criteria are placed in one of two categories. Dispositive criteria are assessed, without exception, to determine whether a validation test passes or fails overall. Diagnostic criteria are assessed, subject to justified exception, to evaluate the quality or degree of some particular aspect of performance. Repeatability – Consistency in achieving passing results is to be demonstrated for each scenario in the representative test set; thus, the minimum number of formal repetitions for each scenario is two.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2020

Physics and technology considerations for the deuterium–tritium fuel cycle and conditions for tritium fuel self sufficiency

The tritium aspects of the DT fuel cycle embody some of the most challenging feasibility and attractiveness issues in the development of fusion systems. The review and analyses in this paper provide important information to understand and quantify these challenges and to define the phase space of plasma physics and fusion technology parameters and features that must guide a serious R&D in the world fusion program. We focus in particular on components, issues and R&D necessary to satisfy three 'principal requirements': (1) achieving tritium self-sufficiency within the fusion system, (2) providing a tritium inventory for the initial start-up of a fusion facility, and (3) managing the safety and biological hazards of tritium. A primary conclusion is that the physics and technology state-of-the-art will not enable DEMO and future power plants to satisfy these principal requirements. We quantify goals and define specific areas and ideas for physics and technology R&D to meet these requirements. A powerful fuel cycle dynamics model was developed to calculate time-dependent tritium inventories and flow rates in all parts and components of the fuel cycle for different ranges of parameters and physics and technology conditions. Dynamics modeling analyses show that the key parameters affecting tritium inventories, tritium start-up inventory, and tritium self-sufficiency are the tritium burn fraction in the plasma (f b ), fueling efficiency (η f ), processing time of plasma exhaust in the inner fuel cycle (t p ), reactor availability factor (AF), reserve time (tr) which determines the reserve tritium inventory needed in the storage system in order to keep the plant operational for time t r in case of any malfunction of any part of the tritium processing system, and the doubling time (t d ). Results show that η f f b > 2% and processing time of 1–4 h are required to achieve tritium self-sufficiency with reasonable confidence. For η f f b = 2% and processing time of 4 h, the tritium start-up inventory required for a 3 GW fusion reactor is ~11 kg, while it is <5 kg if η f f b = 5% and the processing time is 1 h. To achieve these stringent requirements, a serious R&D program in physics and technology is necessary. The EU-DEMO direct internal recycling concept that carries fuel directly from the plasma exhaust gas to the fueling systems without going through the isotope separation system reduces the overall processing time and tritium inventories and has positive effects on the required tritium breeding ratio (TBR R ). A significant finding is the strong dependence of tritium self-sufficiency on the reactor availability factor. Simulations show that tritium self-sufficiency is: impossible if AF < 10% for any η f f b , possible if AF > 30% and 1% ≤ η f f b ≤ 2%, and achievable with reasonable confidence if AF > 50% and η f f b > 2%. These results are of particular concern in light of the low availability factor predicted for the near-term plasma-based experimental facilities (e.g. FNSF, VNS, CTF), and can have repercussions on tritium economy in DEMO reactors as well, unless significant advancements in RAMI are made. There is a linear dependency between the tritium start-up inventory and the fusion power. The required tritium start-up inventory for a fusion facility of 100 MW fusion power is as small as 1 kg. Since fusion power plants will have large powers for better economics, it is important to maintain a 'reserve' tritium inventory in the tritium storage system to continue to fuel the plasma and avoid plant shutdown in case of malfunctions of some parts of the tritium processing lines. But our results show that a reserve time as short as 24 h leads to unacceptable reserve and start-up inventory requirements. Therefore, high reliability and fast maintainability of all components in the fuel cycle are necessary in order to avoid the need for storing reserve tritium inventory sufficient for continued fusion facility operation for more than a few hours. The physics aspects of plasma fueling, tritium burn fraction, and particle and power exhaust are highly interrelated and complex, and predictions for DEMO and power reactors are highly uncertain because of lack of experiments with burning plasma. Fueling by pellet injection on the high field side of tokamak has evolved to be the preferred method to fuel a burning plasma. Extrapolation from the DIII-D penetration scaling shows fueling efficiency expected in DEMO to be <25%, but such extrapolations are highly uncertain. The fueling efficiency of gas in a reactor relevant regime is expected to be extremely poor and not very useful for getting tritium into the core plasma efficiently. Gas fueling will nonetheless be useful for feedback control of the divertor operating parameters. Extensive modeling has been carried out to predict burn fraction, fueling requirements, and fueling efficiency for ITER, DEMO, and beyond. The fueling rate required to operate Q = 10 ITER plasmas in order to provide the required core fueling, helium exhaust and radiative divertor plasma conditions for acceptable divertor power loads was calculated. If this fueling is performed with a 50–50 DT mix, the tritium burn fraction in ITER would be ~0.36%, which is too low to satisfy the self-sufficiency conditions derived from the dynamics modeling for fusion reactors. Extrapolation to DEMO using this approach would also yield similarly low burn fraction. Extensive analysis presented shows that specific features of edge neutral dynamics in ITER and fusion reactors, which are different from present experiments, open possibilities for optimization of tritium fueling and thus to improve the burn fraction. Using only tritium in pellet fueling of the plasma core, and only deuterium for edge density, divertor power load and ELM control results in significant increase of the burn fraction to 1.8–3.6%. These estimates are performed with physics models whose results cannot be fully validated for ITER and DEMO plasma conditions since these cannot be achieved in present tokamak experiments. Thus, several uncertainties remain regarding particle transport and scenario requirements in ITER and DEMO. The safety standard requirements for protection of the public and release guidelines for tritium have been reviewed. General safety approaches including minimizing tritium inventories, reducing tritium permeation through materials, and decontaminating material for waste disposal have been suggested.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Common Approach to Molten Salt Reactor Safety Evaluation [Slides]

The presentation describes the necessary elements of developing a common approach to molten salt reactor (MSR) safety adequacy evaluation. Developing a common approach to establishing adequate safety for MSRs could substantially decrease the developer risks. However, safety adequacy is intimately associated with reactor licensing which is an element with national sovereignty. No reactor class has a common, portable international license. The advantageous performance characteristics of MSRs can be leveraged to decrease the cost and time necessary to develop reasonable confidence of adequate safety. Adequate safety can be demonstrated though either accident prevention or mitigation. MSR have characteristics that may make accident mitigation a preferable safety adequacy evaluation approach. Adequate quality as well as a thorough understanding of accident progression validated through separate and integral effects testing remains central to any safety adequacy demonstration method.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Initial PIP-II Beam Current Monitor Fault Case Analyses & Beam Position Monitor Linearity Studies in CST Studio Suite

The use of non-invasive sensors & systems to measure particle beam characteristics is a crucial part of modern accelerator control systems due to their ability to return real time beam data while minimizing negative effects on beam quality. To ensure that one can be reasonably confident these sensors will behave as desired upon be-ing implemented within the beamline, simulations pre-dicting the performance of these sensors under beamline conditions can be used as a valuable tool for checking sensor functionality without a physical test bench. This paper details the design, testing, and results of two sensor models developed using CST Studio Suite soft-ware designed to mimic two sensors to be implemented within the PIP-III beamline: an elliptical, large-aperture beam position monitor (BPM) for which vertical & hori-zontal position signal linearity was analyzed, and an AC current transformer (ACCT) beam current monitor (BCM) used to search for potential fault cases within the BCM and beam pipe flange gaps. Special focus is given to the discovery of linearity variations within the BPM and the use of frequency domain techniques in the BCM fault case analyses.

Rouzky, A. R.↗
DOE OSTI2024

Durability testing of actual Hanford waste glasses and their non-radioactive simulant glasses

The low-activity waste (LAW) fraction of Hanford tank waste will be converted to glass at the Waste Treatment and Immobilization Plant (WTP) and disposed on the Hanford site. The chemical durability of LAW glasses has been researched for decades to satisfy contract requirements. Most LAW glass durability data has been generated on non-radioactive simulant glasses fabricated via crucible melts. These non-radioactive glasses were chosen due to safety and cost reasons with confidence that radioactive waste glasses would exhibit similar behavior. To reduce the risk of significant differences in laboratory test response data between WTP melter waste glass and simulant glass, Product Consistency Tests (PCT, i.e., ASTM C1285-21) and Environmental Protection Agency (EPA) 1313 durability tests were performed on actual and simulant LAW glasses fabricated using laboratory-scaled melters. Actual and simulant glass durability test results are presented and statistically compared. Finally, differences in test responses were found to be within experimental uncertainty.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2022

Method for Generating Expert Derived Confidence Scores

We executed a pilot demonstration of a methodology for developing a new confidence metric to help operators calibrate their trust in ML event classifiers. This confidence metric was derived from domain expert judgment and was accompanied with a qualitative description describing the reason for each confidence rating. After learning the boundaries of an ML’s performance by studying a subset of events an SME rated his confidence in the ML’s ability to classify similar events and provided an explanation for his ratings. To demonstrate this methodology, we developed our expert driven confidence scores for the ML event classifier within the ESAMS. Next, we assessed the accuracy of the human expert confidence scores relative to the ML’s uncertainty quantification scores. This report includes a description of our methodology, summary of our findings and future directions.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

When less is more: How increasing the complexity of machine learning strategies for geothermal energy assessments may not lead toward better estimates

Previous moderate- and high-temperature geothermal resource assessments of the western United States utilized data-driven methods and expert decisions to estimate resource favorability. Although expert decisions can add confidence to the modeling process by ensuring reasonable models are employed, expert decisions also introduce human and, thereby, model bias. This bias can present a source of error that reduces the predictive performance of the models and confidence in the resulting resource estimates. Our study aims to develop robust data-driven methods with the goals of reducing bias and improving predictive ability. We present and compare nine favorability maps for geothermal resources in the western United States using data from the U.S. Geological Survey's 2008 geothermal resource assessment. Two favorability maps are created using the expert decision-dependent methods from the 2008 assessment (i.e., weight-of-evidence and logistic regression). With the same data, we then create six different favorability maps using logistic regression (without underlying expert decisions), XGBoost, and support-vector machines paired with two training strategies. The training strategies are customized to address the inherent challenges of applying machine learning to the geothermal training data, which have no negative examples and severe class imbalance. We also create another favorability map using an artificial neural network. We demonstrate that modern machine learning approaches can improve upon systems built with expert decisions. We also find that XGBoost, a non-linear algorithm, produces greater agreement with the 2008 results than linear logistic regression without expert decisions, because the expert decisions in the 2008 assessment rendered the otherwise linear approaches non-linear despite the fact that the 2008 assessment used only linear methods. The F1 scores for all approaches appear low (F1 score < 0.10), do not improve with increasing model complexity, and, therefore, indicate the fundamental limitations of the input features (i.e., training data). Until improved feature data are incorporated into the assessment process, simple non-linear algorithms (e.g., XGBoost) perform equally well or better than more complex methods (e.g., artificial neural networks) and remain easier to interpret.

15 GEOTHERMAL ENERGY↗
DOE OSTI2025

Early Stages in the Lifecycle of Polar Liquid-Bearing Clouds

Stratiform liquid-bearing clouds are ubiquitous over the polar regions, where they are predominantly mixed-phase. These polar clouds induce substantial radiative forcing on the surface and continuously modify the atmospheric thermodynamic budget, with direct implications for the polar ice pack resilience. However, the physical representation of these clouds is still a major challenge for climate models. A significant part of polar liquid-bearing cloud lifecycle is often manifested in a quasi-steady self-sustaining, persistent, and turbulent state, which is driven by longwave cloud radiative cooling and can last for multiple days. This self-sustaining cloud lifecycle stage has been thoroughly investigated in numerous studies, though some of its aspects such as precipitation still lack robust quantification and evaluation. The preceding cloud lifecycle stages, which may last up to several hours, have nonetheless remained widely overlooked. These preceding stages initiate at cloud formation, often in a stable and non-turbulent atmospheric layer and serve as a key junction between cloud persistence and cloud dissipation. These two contrasting cloud lifecycle trajectories pose the question if general circulation models (GCMs) can capture the full lifecycle accurately for the real physical reasons, a necessary condition to improve our confidence in climate projections given the changing polar climate. The purpose of this project was to improve the characterization and understanding of these early stages in the lifecycle of polar stratiform liquid-bearing cloud and to aid their representation in GCMs. This research relied on measurements from the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) field campaign, as well as the observations from the ARM West Antarctic Radiation Experiment (AWARE) and the permanent ARM site at Utqiagvik, North Slope of Alaska (NSA).

58 GEOSCIENCES↗
DOE OSTI2022

Representative-cell-based Modeling of HTTF in SAM

Although the current nuclear power market is primarily occupied by the light water reactors (LWRs), the TRISO-fueled helium-cooled graphite-moderated high temperature gas reactors (HTGRs) are drawing growing attention as the nuclear power industry marches towards more advanced systems. Compared to that of conventional LWRs, the thermal hydraulics of HTGR cores show extra complexity from their multi-scale heat transfer mechanisms with varying importance during different operation modes or transient stages. The modeling of HTGR cores for the system analysis purpose therefore faces the challenge of reaching reasonable fidelity and accuracy while maintaining sufficient simplicity. Previous development and validation efforts have demonstrated that a “2-D ring model” with reasonable performance can be implemented in the System Analysis Module (SAM) for prismatic HTGR cores. In the current project, an alternative modeling methodology based on “representative cells” is proposed for the typical prismatic core of HTGRs. Different from the previous ring model approach, the proposed methodology first separately models and then combines the small- and large-scale thermal conductions, by connecting representative local heat transfer units (cells) with effective core- wise thermal resistance. A modeling practice for an integral high-temperature test facility (HTTF) elaborates the modeling details. Steady-state validation of the resultant candidate model is performed against a higher-resolution benchmark from a 3D-1D coupled simulation, which shows satisfactory prediction with reasonably captured global parameters and well-represented temperature fields. A postulated pressurized conduction cooldown (PCC) is also simulated and analyzed, demonstrating the model’s capability of transient prediction with physically captured phenomena resolved in both small and large temporal and spatial scales. In general, the current work achieves a preliminary success in proposing a methodology using representative cells to model prismatic HTGR cores in SAM. Future efforts are envisioned with more validation activities and with potential modeling improvements to eventually achieve the high confidence on a high-fidelity robust modeling methodology with reasonable accuracy.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2020

Foliar functional traits from imaging spectroscopy across biomes in eastern North America

Summary Foliar functional traits are widely used to characterize leaf and canopy properties that drive ecosystem processes and to infer physiological processes in Earth system models. Imaging spectroscopy provides great potential to map foliar traits to characterize continuous functional variation and diversity, but few studies have demonstrated consistent methods for mapping multiple traits across biomes. With airborne imaging spectroscopy data and field data from 19 sites, we developed trait models using partial least squares regression, and mapped 26 foliar traits in seven NEON (National Ecological Observatory Network) ecoregions (domains) including temperate and subtropical forests and grasslands of eastern North America. Model validation accuracy varied among traits (normalized root mean squared error, 9.1–19.4%; coefficient of determination, 0.28–0.82), with phenolic concentration, leaf mass per area and equivalent water thickness performing best across domains. Across all trait maps, 90% of vegetated pixels had reasonable values for one trait, and 28–81% provided high confidence for multiple traits concurrently. Maps of 26 traits and their uncertainties for eastern US NEON sites are available for download, and are being expanded to the western United States and tundra/boreal zone. These data enable better understanding of trait variations and relationships over large areas, calibration of ecosystem models, and assessment of continental‐scale functional diversity.

Wang, Zhihui↗
DOE OSTI2025

Modeling of Stress and Temperature Effects on Creep of Reduced Activation Ferritic-Martensitic Steel Alloy F82H (Tertiary Creep Modeling of RAFM Steel)

A Bayesian optimization procedure is presented for calibrating a multi-mechanism micromechanical model for creep to experimental data of F82H steel. Reduced activation ferritic martensitic (RAFM) steels based on are the most promising candidates for some fusion reactor structures. Although there are indications that RAFM steel could be viable for fusion applications at temperatures up to 600 °C, the maximum operating temperature will be determined by the creep properties of the structural material and the breeder material compatibility with the structural material. Due to the relative paucity of available creep data on F82H steel compared to other alloys such as Grade 91 steel, micromechanical models are sought for simulating creep based on relevant deformation mechanisms. As a point of departure, this work recalibrates a model form that was previously proposed for Grade 91 steel to match creep curves for F82H steel. Due to the large number of parameters (9) and cost of the nonlinear simulations, an automated approach for tuning the parameters is pursued using a recently developed Bayesian optimization for functional output (BOFO) framework [1]. Incorporating extensions such as batch sequencing and weighted experimental load cases into BOFO, a reasonably small error between experimental and simulated creep curves at two load levels is achieved in a reasonable number of iterations. Validation with an additional creep curve provides confidence in the fitted parameters obtained from the automated calibration procedure to describe the creep behavior of F82H steel at 600 °C. The model is further extended using a temperature dependent scaling law approach to simulate creep response between 550 °C and 650 °C. The efficacy of this extension is compared with the previously used scaling law approach for Grade 91 steel.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Multi-year incubation experiments boost confidence in model projections of long-term soil carbon dynamics

Abstract Global soil organic carbon (SOC) stocks may decline with a warmer climate. However, model projections of changes in SOC due to climate warming depend on microbially-driven processes that are usually parameterized based on laboratory incubations. To assess how lab-scale incubation datasets inform model projections over decades, we optimized five microbially-relevant parameters in the Microbial-ENzyme Decomposition (MEND) model using 16 short-term glucose (6-day), 16 short-term cellulose (30-day) and 16 long-term cellulose (729-day) incubation datasets with soils from forests and grasslands across contrasting soil types. Our analysis identified consistently higher parameter estimates given the short-term versus long-term datasets. Implementing the short-term and long-term parameters, respectively, resulted in SOC loss (–8.2 ± 5.1% or –3.9 ± 2.8%), and minor SOC gain (1.8 ± 1.0%) in response to 5 °C warming, while only the latter is consistent with a meta-analysis of 149 field warming observations (1.6 ± 4.0%). Comparing multiple subsets of cellulose incubations (i.e., 6, 30, 90, 180, 360, 480 and 729-day) revealed comparable projections to the observed long-term SOC changes under warming only on 480- and 729-day. Integrating multi-year datasets of soil incubations (e.g., > 1.5 years) with microbial models can thus achieve more reasonable parameterization of key microbial processes and subsequently boost the accuracy and confidence of long-term SOC projections.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

A Custom Machine to Convey Radiologically Impacted Cohesive Soils to the Orion ScanSortSM System - 20382

An established method to reduce the volume of material required to be disposed of as radioactive waste is conveyor-based sorting of potentially radiologically impacted soils. With the Orion ScanSortSM system, potentially impacted soils are conveyed beneath radiation detectors and sorted into above and below criteria bins based on the detectors' response. Confident measurements can only be efficiently achieved when the soil column being conveyed has a reasonably consistent geometry. Highly cohesive soils present a very significant challenge as they tend to clump and adhere to the conveyor hopper, strike-off bar, and belt skirting. This causes voids and valleys in the soil column that affect the measurement geometry and reduce the confidence in the measurement. The reduction in confidence necessitates a longer residence time (i.e. reduction in conveyor belt speed and processing rates) or that the soils in highly unfavorable geometries be dispositioned as impacted or segregated for resurvey (should site logistics support that option). These outcomes may increase the volume of material required to be dispositioned as radiological waste and have a negative impact on project cost and schedule. To minimize impact to sorting operations, Wood designed and built a customized Extruder, to optimize the soil column prior to assay. The design was developed and refined to minimize the volume of highly cohesive soils presented in highly unfavorable geometries in the soil column in order to confidently assess and disposition such soils in a high-production environment. The Extruder is a customized 90 cm wide flat conveyor that has an oversized hopper with a pair of motor-driven rollers that force the soils in the hopper through an opening of adjustable height. The soils are extruded through the opening to produce a soil column that is ∼75 cm wide and ∼8-18 cm deep with a design rate of 225 metric tons/hr. The Extruder was recently deployed with the Orion ScanSort{sup SM} System to a site in northeast Ohio. The site has highly cohesive soils that result from the weathering of glacial sediments and consist of clay and clay loam, resulting in poor drainage and high moisture content. The project infrastructure only supported two bins of material (above and below criteria), which necessitated that soils with unfavorable geometries be discharged into the above criteria bin, along with material determined to have been contaminated. The Extruder was extremely successful in producing a stable soil column with favorable geometries for radiological assay. During production, less than 0.5% (by mass) of the soils processed were presented in unsatisfactory geometries requiring disposition as radioactive waste. The Extruder did not get clogged due to the cohesive soils (as is typical with conventional conveyors) and required very little maintenance, again minimizing impacts to sorting operations. The conveyor belt speed was operated at 14 cm/s with a typical belt loading of ∼109 kg/m resulting in a mean process rate of ∼49 metric tons/hr. The process rate was constrained by other project logistics, rather than by the capabilities of the Extruder, which was operated at less than 20% of the maximum design speed (75 cm/s). It is concluded that the Extruder is highly likely to produce a stable highly cohesive soil column suitable for efficient and confident radiological assay in production environments of 250 short tons/hr or more. The Extruder has the capability to drastically reduce the duration and costs of projects with radiologically impacted highly cohesive soils. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2023

Evaluation of distributed process-based hydrologic model performance using only a priori information to define model inputs

Fully distributed, integrated surface–subsurface hydrological models (ISSHMs) have seen renewed interest due to availability of better software, high performance computing facilities, and high-resolution, spatially extensive data products. ISSHMs are valuable as tools for advancing system understanding as they can resolve multiple processes defined on the plot scale including three-dimensional interaction of surface water and groundwater. Here, we evaluated the performance of an ISSHM, the Advanced Terrestrial Simulator (ATS), on seven diverse catchments across the continental US using widely available data products to define model inputs without calibration. We compare the ATS-simulated streamflow and evapotranspiration with gauge observations and MODIS-derived evapotranspiration, respectively. Using the Kling-Gupta Efficiency (KGE) as metric, ATS with default data products performed reasonably well at 6 of 7 catchments for streamflow. However, in one of those 6 catchments ATS had poor performance on baseflow and ATS’s overall performance was thus judged to be inadequate despite the acceptable KGE. ATS performance for evapotranspiration was good in all 7 catchments using default data products. In the two catchments where ATS streamflow performance using default data products was not acceptable, the performance was significantly improved by using local information on subsurface properties below the soil. We also compare the model-simulated streamflow and evapotranspiration with the Sacramento soil moisture accounting (SAC-SMA) model, a semi-distributed model that was calibrated on a catchment-by-catchment basis. Uncalibrated ATS performance is comparable to the calibrated SAC-SMA model in terms of streamflow while ATS performance is similar to or better (much better in certain catchments) in reproducing MODIS-derived evapotranspiration. Reasonably good performance of ATS without catchment-specific calibration provides new confidence in the ISSHM class of models and community data products as tools for advancing understanding of watershed function in a changing environment.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Sensitivity of the simulation of passive neutron emission from UF 6 cylinders to the uncertainties in both 19 F(α,n) energy spectrum and thick target yield of 234 U in UF 6

Interest in safeguards verification measurements using passive thermal neutron counting to assay 235 U content in large 30B UF 6 canisters has grown in recent years. Here, the prohibitively high cost and impracticality of using reference 30B calibration cylinders extensively will likely make accurate simulations of increasing interest. Accuracy of the simulated response will define the confidence in the predicted response and the extent to which simulations can reasonably be relied upon. With 234 U driven 19 F(α, n) reactions being the main neutron source in low enriched UF 6 the uncertainties of the 19 F(α, n) energy spectrum and the thick target yield of 234 U in UF 6 propagate into the uncertainty in the predicted response and represent a major influence of basic nuclear data. Here sensitivity of the simulated total (Singles) and coincidence (Doubles) count rates are assessed for the Passive Neutron Enrichment Meter using six potential 19 F(α, n) neutron energy spectra over a range of enrichments and material distributions. The results indicate that variations in the Singles and Doubles due to simulated (α, n) neutron spectrum are less than 1.5% for this set of simulated neutron spectra, with dependence varying inversely with enrichment. Singles uncertainty is only slightly less than that of the thick target 19 F(α, n) yield corresponding to the primary neutron source, whereas the 19 F(α, n) yield dependence of the Doubles is reduced by the non-negligible 238 U(SF) coincident neutron emissions. Based on available thick target 19 F(α, n) yield estimates the uncertainty is on the order of 5%, establishing this as the main nuclear data limitation when simulating thermal neutron detectors response for 30B UF 6 storage cylinders. Based on these findings, it appears that the measurement and evaluation of the thick target 19 F(α, n) yield for uranium hexafluoride is due.

19F(α,n) neutron spectrum↗
DOE OSTI2022

The development of a high-resolution Eulerian radiation-hydrodynamics simulation capability for laser-driven Hohlraums

Hohlraums are hollow cylindrical cavities with high-Z material walls used to convert laser energy into uniform x-ray radiation drives for inertial confinement fusion capsule implosions and high energy density physics experiments. Credible computational modeling of hohlraums requires detailed modeling and coupling of laser physics, hydrodynamics, radiation transport, heat transport, and atomic physics. We report on improvements to Los Alamos National Laboratory's xRAGE radiation-hydrodynamics code in order to enable hohlraum modeling. xRAGE's Eulerian hydrodynamics and adaptive mesh refinement make it uniquely well suited to study the impacts of multiscale features in hohlraums. In order to provide confidence in this new modeling capability, we demonstrate xRAGE's ability to produce reasonable agreement with data from several benchmark hohlraum experiments. We also use xRAGE to perform integrated simulations of a recent layered high density carbon capsule implosion on the National Ignition Facility in order to evaluate the potential impacts of the capsule support tent, mixed cell conductivity methodologies, plasma transport, and cross-beam energy transfer (XBT). We find that XBT, seeded by plasma flows in the laser entrance hole (LEH), causes a slight decrease in energy coupling to the capsule and that all of these impact the symmetry of the x-ray drive such that they have an appreciable impact on the capsule implosion shape.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Calibration of RAFM Micromechanical Model for Creep Using Bayesian Optimization for Functional Output

A Bayesian optimization procedure is presented for calibrating a multimechanism micromechanical model for creep to experimental data of F82H steel. Reduced activation ferritic martensitic (RAFM) steels based on Fe(8–9)%Cr are the most promising candidates for some fusion reactor structures. Although there are indications that RAFM steel could be viable for fusion applications at temperatures up to 600°C, the maximum operating temperature will be determined by the creep properties of the structural material and the breeder material compatibility with the structural material. Due to the relative paucity of available creep data on F82H steel compared to other alloys such as Grade 91 steel, micromechanical models are sought for simulating creep based on relevant deformation mechanisms. As a point of departure, this work recalibrates a model form that was previously proposed for Grade 91 steel to match creep curves for F82H steel. Due to the large number of parameters (9) and cost of the nonlinear simulations, an automated approach for tuning the parameters is pursued using a recently developed Bayesian optimization for functional output (BOFO) framework (Huang et al., 2021, “Bayesian optimization of functional output in inverse problems,” Optim. Eng., 22, pp. 2553–2574). Incorporating extensions such as batch sequencing and weighted experimental load cases into BOFO, a reasonably small error between experimental and simulated creep curves at two load levels is achieved in a reasonable number of iterations. In conclusion, validation with an additional creep curve provides confidence in the fitted parameters obtained from the automated calibration procedure to describe the creep behavior of F82H steel.

42 ENGINEERING↗
DOE OSTI2021

Review of Pantex Radiation Safety Department 2020 Backup Dosimetry Processing Methodology

In the first quarter (Q1) of Calendar Year 2020, the Pantex Radiation Safety Department (Pantex) experienced various issues and failures with their dosimeter processing equipment. Efforts to repair the equipment resulted in limited functionality without the ability to process dosimeters assigned to personnel for monitoring dose. As a result of the impairments to the dosimeter processing equipment, Pantex called upon Nevada National Security Site (NNSS) for support, as their designated backup processor. In January of 2021, LLNL Subject Matter Experts in External Dosimetry started an NNSA-requested review of Pantex’s personnel doses in Q1 2020. Its focus was the technical validity of the means and methods used by Pantex and its conclusions and provide a level of confidence to National Nuclear Security Administration (NNSA) that the resulting personnel doses were reasonable, conservative, and defensible.

61 RADIATION PROTECTION AND DOSIMETRY↗